A coordination control strategy based on stability judgment is presented for autonomous vehicles (AVs) aiming to enhance the handling and stability performance. Firstly, the stability judgment scheme is used to evaluate the real-time stability level of vehicles based on the Self-Organizing Feature Map (SOFM) neural network and K-Means algorithm. Secondly, a coordination controller of active front steering (AFS) and direct yaw moment control (DYC) is designed to track the desired vehicle motion. To enhance the handling and stability of AVs, the weights of AFS and DYC controllers are adaptively adjusted according to the vehicle stability level. Finally, the effectiveness of the proposed method is verified in co-simulation environment of CarSim and Simulink, and a rapid control prototyping test is implemented to evaluate the feasibility and robustness. The results indicate that the stability judgment scheme and coordination control strategy for AVs can not only satisfy the requirements of path tracking accuracy but also enhance the handling and stability performance.
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